Search

This paper investigates the adaptive consensus with limited information for a class of uncertain nonlinear multi-agent systems (MASs). The limited information, meaning the incomplete information transmitted between agents, stems from nonzero-kernel weight matrices of communication networks, which deserves concerns owing to its practical interest such as in privacy preserving and information compression. Apart from the limited/incomplete information, the paper considers nonlinear MASs with large uncertainties (without known upper bounds). This is essentially different from the existing results of linear systems and poses challenges for the design and analysis of adaptive consensus. As for fully distributed protocol design, dynamic high gains are introduced to compensate for the system uncertainties and for the unavailable global graph information. In closed-loop consensus analysis, a new Lyapunov function is constructed by utilising weight and incidence matrices instead of Laplacian matrix. It turns out that the designed protocol can guarantee the boundedness of closed-loop MASs signals and the convergent consensus. Two numerical examples are given to demonstrate the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

This paper aims at adaptive event-triggered output-feedback stabilisation in the presence of intractable non-parametric uncertainties. Typically, double-side (i.e. sensor-to-controller and controller-to-actuator) event-triggered communication is pursued for efficient resource utilisation, unlike in related works only reducing single-side communication. This renders more constrained information transmitted via network, challenging the co-design of the compensation and event-triggering mechanisms. By incorporating a switching-varying mechanism, a distinctive adaptive event-triggered output-feedback scheme is established based on a switching filter reconstructing the unmeasurable states. Crucially, a convergence-preserving event-triggering mechanism is proposed with the adaptiveness for uncertainty compensation, by suitably exploiting the switching-varying gain. As such, a desired event-triggered output-feedback control is designed with linearity (with respect to the system output and the filter states) rendered for the controller signal. Just owing to the linearity, the controller signal is subtly kept from entering the event-triggering mechanism, so as to match the double-side event-triggered architecture. Furthermore, it is achieved that the system and filter states converge to zero while a positive minimum inter-execution time is ensured. [ABSTRACT FROM AUTHOR]

This research focuses on the under-studied phenomenon of maritime borders by providing a civilian perspective on how fishers live, negotiate, contest, and transcend state borders and surveillance at sea. It explores the everyday transboundary practices of Chinese fishers in the geopolitically sensitive South China Sea (SCS), examining their cross-border tactics to sustain fishing livelihoods and the mechanisms underpinning these tactics. Based on long-term, continuous ethnographic investigations, we unravel four tactics employed by Chinese fishers to elude the constraints of territorial borders: contract production, trans-territorial production, paying for the sea, and the appropriation of marine physicality. These transboundary strategies are supported by three mechanisms, including common fisher identity, historical transnational networks, and regional development structures. This research shows the agency and creativity of fishers in challenging and punctuating maritime territoriality in the context of increasing militarisation and securitisation of borderlands. It illustrates how the distinct materiality, mobility, and temporality of the ocean can be weaponised by fishers to undermine state-bordering processes. By exposing the extensive, dynamic, and complex civilian interactions and collaborations in the region, we demonstrate that the SCS is more than a geopolitical space but at the same time a social site of cooperation and solidarity. In doing so, this research contributes to studies of maritime borders and civilian geopolitical subjectivity by illuminating the flexibility of fishers in exercising powers on borders at sea. It also advances the existing SCS area studies by 'peopling' the political geography of the region. [ABSTRACT FROM AUTHOR]

Summary: The connectivity of communication graph is indispensable for consensus of multi‐agent systems (MASs), which in many applications (e.g., wireless sensor) depends on the relative distances between agents. But, in the adaptive setting particularly with system nonlinearities and event‐triggered communication, it is rather difficult to enforce the relative distances within the limited range for the connectivity. This paper focuses on developing an adaptive event‐triggered control strategy with connectivity preservation in the context of nonidentical unknown control coefficients and heterogeneous nonlinearities coupling with parameter uncertainties. First, a group of potential functions are introduced acting as control barrier functions to constrain the relative distances between agents within the limited range for all time. Also, two dynamic gains are specialized for each agent to handle the system uncertainties, system nonlinearities and negative effect of the execution error. Then, an adaptive event‐triggered protocol is designed for each agent such that the connectivity‐preserving consensus of MASs is achieved and Zeno behavior is excluded. Moreover, an extended study is conducted on a leader‐following scenario. Two simulation examples illustrate the effectiveness of the proposed event‐triggered control strategy. [ABSTRACT FROM AUTHOR]

Summary In this paper, we investigate the global adaptive stabilization problem via partial‐state feedback for a class of uncertain chained‐form nonholonomic systems with the dynamic uncertainty and nonlinear parameterization. The notions of Sontag's input‐to‐state stability (ISS) and ISS‐Lyapunov function, together with the changing supply rates technique are used to overcome the dynamic uncertainty. The nonlinear parameterization is well treated with the aid of the parameter separation technique. The discontinuous input‐to‐state scaling technique is employed in this procedure to derive the global stabilization controllers. Additionally, we develop a switching adaptive control strategy in order to get around the smooth stabilization burden associated with nonholonomic systems. The simulation results illustrate the efficacy of the presented algorithm. [ABSTRACT FROM AUTHOR]

The paper considers adaptive event‐triggered control for nonlinear systems with time‐varying parameter uncertainties. The time‐varying uncertainties do not need to be differentiable, but their variation amplitudes are required to be known. Such uncertainties appear not only in the system nonlinearities but also as the control coefficient. We pursue a tight design scheme by combining tuning functions and the congelation of variables method, thereby avoiding the overuse of dominations and obtaining a less conservative controller. In view of the essence of the control problem, we don't design a continuous controller first and then search for a complex and suitable event‐triggering mechanism, as emulation methods done in the literature. In contrast, we adopt a simple event‐triggering mechanism with the relative threshold, while seeking a complex and appropriate adaptive controller which contains the new adaptive treatment for execution error due to the unknown time‐varying control coefficient. Note that there are three parameter dynamic compensators in the adaptive controller, and one is specialized to the execution error, which is not required in the continuous feedback context. It is shown that with the proposed adaptive event‐triggered controller, all the closed‐loop signals are bounded, the system state converges to zero, and no Zeno behavior occurs. A comparative simulation is provided to verify the theoretical results. [ABSTRACT FROM AUTHOR]

Summary: Rapid convergence that can be prescribed by a user is appealing for many applications with high requirements. This stimulates finite‐time stabilization with arbitrarily prescribed settling‐time and so‐called prescribed‐time stabilization. But their continuous realizations had to restrict uncertainties and/or to bear truncated run of controllers. This paper, for nonlinear systems with large uncertainties, realizes not only the convergence within the prescribed time, but also the non‐truncated run. First, by lending finite‐time stabilization to prescribed‐time stabilization and integrating dynamic compensation, an adaptive controller with time‐varying components is devised such that the system state reaches the origin at a finite time less than the prescribed time, while exhibiting local asymptotic stability (of the origin). Then by monitoring the finite time online, the time‐varying components of the adaptive controller are frozen as their values at the finite time. The asymptotic stability guarantees the frozen adaptive controller can make the system state remain at the origin for all future time. But the above finite time could not be detected in practice, due to ubiquitous disturbances. We thus modified the detection to ensure that the system state enters a vicinity of the origin before the prescribed time and stays there afterwards under some conditions on uncertainties and disturbances. Two simulation examples illustrate the effectiveness of the proposed controller. [ABSTRACT FROM AUTHOR]

This research examines the geopolitical entanglements of China's tourism in the South China Sea (SCS) and the geopolitical implications of uneven mobility rights on tourists' geopolitical subjectivation. We show that maritime territorialisation in the SCS is mobile and constituted by tourism mobilities. However, although tourism mobility control constitutes and performs state territorialisation, it also generates unsatisfied internal bordering effects. We reveal that uneven mobility rights premised on territorial geopolitics are unevenly experienced by tourists. Within the contemporary deeply embedded structure of the territory-nation-state, mobility governance, hierarchy, inequity, and unevenness driven by national interests, security, and secrecy are widely accepted and taken for granted. The encounters and affective engagements of tourism mobility regulations in the SCS, intersecting with everyday experiences of mobility hierarchies as well as state geopolitical processes, contribute to shaping individuals' geopolitical identity. This promotes the internalisation of the contemporary mobility regime and facilitates the naturalisation of state geopolitical competitions. By exploring the geopolitical experiences of selective mobility control and its geopolitical effects on tourists, this research sheds light on the uneven political spatiality of everyday tourism mobilities and offers a more nuanced and intimate understanding of the geopolitics of tourism (im)mobilities at the micro-scale. [ABSTRACT FROM AUTHOR]

This paper typically concerns more efficient event‐triggered implementation, and specifically establishes an adaptive event‐triggered framework to achieve global stabilization for a class of uncertain nonlinear systems while reducing both sensor‐to‐controller and controller‐to‐actuator communication (rather than only one‐side communication). First, a novel switching event‐triggering mechanism is proposed to determine when to transmit information and adjust parameters. Particularly, with the switching varying mechanism incorporated, not only large uncertainties (whose bounds are unknown) but also inherent nonlinearities can be effectively dealt with. Then, a linear simple controller, rather than a complicated nonlinear one as in the related literature, is designed based on the switching event‐triggering mechanism. It turns out that the closed‐loop system states converge to zero while no infinitely fast sampling/execution or infinite switchings occur. Notably, just owing to the linearity of controller function, the controller signal is kept from entering the event‐triggering mechanism, which enables the sensor‐to‐controller event‐triggered communication. Besides, by strengthening the switching varying mechanism, an explicit pre‐evaluation is derived for the lower bound of inter‐execution intervals, in order to ensure moderate communication rates for reliable implementation of the event‐triggered controller. [ABSTRACT FROM AUTHOR]

This paper addresses global output-feedback stabilisation in the context of unknown control directions and intrinsic unmeasurable-states-dependent growth, and focuses on rectifying the substantial deficiencies in the related works and developing a new adaptive output-feedback controller essentially reducing conservativeness. First, a varying parameter which takes value 1 or − 1 , instead of in an unbounded countable set, is specialised to capture the unknown control direction and accordingly a supervisory mechanism is delicately constructed to decide when to switch the parameter from 1 to − 1 or from − 1 to 1. A dynamic high gain, rather than a switching one, is appointed to compensate the serious system uncertainties. Then, the wanted controller is constructed, for which the design functions and design parameters are recursively generated by backstepping method (instead of analytically defined owing to the unknown control coefficients). Based on the designations and supervisory mechanism, it turns out that no Zeno phenomenon occurs, and global boundedness and convergence (to zero) hold, both for the resulting closed-loop system. An example is given to show the effectiveness and the advantage of the proposed scheme. [ABSTRACT FROM AUTHOR]

Whether or not system performance can be prescribed by users is one core issue for almost all control problems, of course for multi‐agent control systems. But it could pose stern constraints on or exceptions to systems and control methods. How can one guarantee the prescribed performance while covering much more systems? It deserves deep study and particularly entails the integration/reformation of the related techniques. In the paper, we are concerned with the leaderless consensus with a prescribed convergence rate, aiming at n$$ n $$‐dimensional multi‐agent systems typically with unknown heterogeneous nonlinearities under a directed graph. In view of the essence of the problem, we resort to a powerful time‐varying high‐gain method, that is, funnel control. Specifically, to suppress unknown system nonlinearities and guarantee the prescribed performance, funnel gains are devised by utilizing the relative states and a time‐varying design function. Integrating them as well as a series of intermediate variables, a distributed consensus protocol is obtained without involving any global graph information. Remark that besides being used to construct funnel gains, the time‐varying design function is also introduced as a part of the protocol, substantially enhancing the control effect and playing a key role in forcing the relative states to ultimately converge to zero. It is shown that under the proposed protocol, the desired consensus is achieved with a prescribed convergence rate. A simulation example is given to illustrate the effectiveness of the theoretical result. [ABSTRACT FROM AUTHOR]

Communication network could suffer uncertainties originating from link faults and network attacks. This situation, in multi-agent systems, can be featured by unknown weights of network topology. To impair the influence of the uncertain topology, typical compensation should be taken into account in distributed protocols to the workability of multi-agent systems. This paper, in the context of uncertain topology, addresses finite-time leader-following consensus for second-order uncertain nonlinear multi-agent systems. In addition to uncertainties in topology, the systems also allow unknown control coefficients, which together with the unknown weights renders the realisation of finite-time leader-following consensus nontrivial. Specifically, a fully distributed protocol based on distributed finite-time observer is designed via integrating the adaptive compensation scheme. Notably, in the designed protocol, dynamic high gains are introduced for the compensations of the network uncertainties and agents uncertainties. It turns out that the designed fully distributed protocol guarantees the global finite-time leader-following consensus. Simulation examples are provided to illustrate the validity of the proposed approach. [ABSTRACT FROM AUTHOR]

Event-triggered control, as networked systems are popular, is increasingly appreciated. Such control could arouse essential saving of communication/computation and would lay the groundwork for networked (control) systems. However, due to the discontinuity and hybrid nature of event-triggered control, the exclusion of Zeno phenomenon is the premise of its workability. Aiming to circumvent the Zeno behaviour more explicitly, we attach a dynamic dwell time to triggering mechanism and propose a new adaptive event-triggered control scheme for uncertain nonlinear systems. Specifically, a set of dynamic gains are first introduced to compensate for large uncertainties and nonlinearities, and the indispensability of a set of gains rather than a gain is elaborated on. Then, from a dynamic-gain-dependent monitoring rule, the positive dwell time is generated so that the Zeno phenomenon can be excluded automatically. In particular, the rule enables system behaviour to be always monitored by evaluating the sampling errors of gains. Based on this, we construct an adaptive controller with linear structure, which allows the execution error can be estimated explicitly, and in turn suppressed by the gains. It is shown that, with the proposed event-triggered control, all the closed-loop system signals are bounded and the system state ultimately converges to zero. Notably, the designed triggering mechanism could save more resources in theory since the event detection and gains monitoring are performed alternately. The effectiveness and superiority of the proposed scheme is illustrated by two simulation examples. [ABSTRACT FROM AUTHOR]

Summary: This article investigates global finite‐time stabilization with prescribed output convergence for uncertain nonlinear systems. It is possible to achieve finite‐time stabilization via continuous adaptive feedback for the systems, but the transient performance could not be prescribed for such feedback. Although funnel control is capable of tackling serious uncertainties and ensuring prescribed performance (such as convergence rate and overshoot), it alone cannot achieve (global) finite‐time stabilization. To this end, we present an integrated controller to achieve the desirable stabilization, retaining the respective advantages of the above two schemes and circumventing their own disadvantages. Specifically, based on the funnel control scheme with suitable design parameters, the system output converges from any initial value to an arbitrarily adjustable region with the prescribed convergence rate before a pregiven time instant, while the system states keep bounded. The adaptive controller, in conjunction with a time‐dependent function, ensures that the system output and states converge to zero in finite time, and particularly the system output with prescribed convergence rate evolves within the prespecified envelope. The effectiveness of the proposed scheme is illustrated by two simulation examples. [ABSTRACT FROM AUTHOR]

This article is devoted to the global output‐feedback stabilization of nonlinear systems with unknown control directions and unmeasured states dependent growth whose rate is an unknown arbitrary function of output. In view of limited capability of continuous feedback in compensating system uncertainties and nonlinearities, a novel switching adaptive scheme is proposed. The scheme involves a logic‐based switching mechanism, based on which, a proper controller is selected (from a family of candidate controllers) to act on the system during its execution interval. The main differences between the proposed scheme and those in the related works are as follows. First, the set of candidate controllers is determined online, rather than specified in advance, which provides foundations for compensating arbitrary function‐of‐output growth rate. Second, an iterative function composed of system memory signals is introduced into the switching mechanism, aiming to evaluate the differences between the system states and observe states. Finally, when switching stops, only by introducing an extra transformation and adopting elaborate analysis, can the boundedness of the closed‐loop system signals be obtained, rather than those in the related works where the boundedness can be naturally established once switching stops. The constructed switching adaptive controller guarantees that all the signals of the resulting closed‐loop system are bounded and ultimately converge to zero. [ABSTRACT FROM AUTHOR]

Stabilisation via adaptive feedback is investigated for an ODE system cascaded by coupled parabolic equations. The remarkable characteristic of the system is the presence of serious uncertainties since no known or bounded intervals are needed for the unknown parameters. Besides, strong coupling exists in the PDE subsystem which brings essential difference compared with those of the related literature. For this, a passive identifier is skillfully constructed firstly, and in turn adaptive laws are given to compensate the serious parametric unknowns. Then, by constructing a backstepping transformation and its inverse one, the identifier joint with the original system is transformed into a new system. From the new system, an adaptive state-feedback controller is designed which ensures that all the states of the closed-loop system are bounded and particularly those of the original system converge to zero. Finally, a numerical example is provided to validate the proposed algorithm. [ABSTRACT FROM AUTHOR]

China's new town and ghost city phenomenon has attracted interest from academics and the media since the 2010s. There is, however, little research on the lived experiences of people in new towns, or of the transformation of these new towns. This paper uses Lefebvre's spatial triad to examine how the spaces of the new town are produced and transformed by interactions between multiple actors. Using an analytical framework based on the spatial triad, we explore the interactive mechanisms and the dialectical relationships within the triad. Taking Kangbashi, a new town in Ordos, Inner Mongolia, as a case study, we explore how the spatial production of a new town is co-created by multiple actors, and local government-led conceived space plays a dominant role in that creation. Through interactions in the dynamic nexus of conceived-perceived-lived space, the new town space is in the process of transformation from an empty "ghost city" to a comfortable habitable city. This research deepens our understanding of new towns and production of space by connecting state-led and capital-driven urban construction with the lived practices of residents. Moreover, this empirical Chinese study contributes to knowledge and understanding across diverse global urban contexts. • An analytical framework based on the spatial triad is proposed. • The mechanisms for the transformation of a new town space from a ghost city to a more habitable city is examined. • The local government dominates both the production of space and its transformation in the new town. [ABSTRACT FROM AUTHOR]

This article investigates the event‐triggered stabilization for a class of hyperbolic PDE‐ODE cascade systems with nonlocal term. The presence of unknown parameters in the system brings technical challenges from design to analysis. This compels us to integrate certain powerful dynamic compensation into event‐triggering control mechanism. To solve the problem, by adaptive technique, a compensation strategy is developed to counteract the parametric uncertainties. Then, a desired event‐triggered controller is delicately designed to guarantee that all the signals in the closed‐loop system are bounded and the original system states converge to zero in the L2 norm. Particularly, the event‐triggering mechanism with an additional dynamic signal in the threshold is devised to overcome the negative influence of execution error, while ensuring a positive lower bound for the interexecution intervals. Finally, a simulation example is given to illustrate the effectiveness of the proposed control strategy. [ABSTRACT FROM AUTHOR]

This paper is devoted to the output-feedback stabilisation for a class of wave equations. Remarkably, only one boundary measurement corrupted by disturbance is available for feedback, and the boundary condition at the control end is dynamic, rather than static. This renders the control problem more challenging than those in the related literature, largely because certain reconstruction and compensation mechanisms respectively for the state and disturbance are necessary but difficult to integrate with the control design for dynamic boundary condition. For this, a powerful adaptive output-feedback stabilising scheme is proposed. Specifically, a delicate observer is constructed for the state in the space domain, with which a dynamic estimate for the disturbance is incorporated. Then, a desired output-feedback controller is designed by backstepping method, which renders the states of the original system and observer to converge to zero, while the estimate of the unknown disturbance converges to its true value. [ABSTRACT FROM AUTHOR]

This article is devoted to the optimal protocol for the leader-following consensus of second-order multiagent systems. Remarkably, the global consensus cost functional and the directed topology are pregiven, and the optimal protocol to be sought is distributed. This makes the Riccati-based strategies inapplicable, by which merely centralized protocol can be derived. As the main contribution of this article, an effective strategy of seeking a distributed optimal protocol is proposed for second-order agents over the digraph of the directed tree. Detailedly, the feasibility of distributed optimal protocol is first affirmed, that is, the existence of optimal gain parameters can be guaranteed. Then, by recursively deriving the completely explicit formulas of the consensus errors of relative position and velocity, an online implementable algorithm is developed to achieve the parameterization of the cost functional, that is, to obtain the explicit formula of the cost functional with respect to gain parameters of all agents. Lastly, the desired optimal gain parameters are obtained by minimizing the explicit formula. [ABSTRACT FROM AUTHOR]

This paper addresses the global stabilisation via adaptive event-triggered output-feedback for a class of uncertain nonlinear systems. Remarkably, the systems under investigation simultaneously allow large uncertainties and linearly unmeasured states dependent growth for the first time in the event-triggered framework, for which a dynamic high gain and an observer based on the high gain are introduced. By integrating compensation and time-varying strategies, an adaptive event-triggered output-feedback controller is established. Particularly, a new event-triggering mechanism is introduced, in which the time-varying threshold (strictly positive and gradually decaying) is key to ensure the validity of the event-triggered controller and achieve the convergence. A simulation example is given to illustrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

Summary: The paper is devoted to the asymptotic output consensus for a class of uncertain nonlinear multi‐agent systems. The disturbance that the system suffered is said to be "atypical" since, unlike the related literature, it is unnecessarily continuously differentiable (e.g., sawtooth wave), and even permitted to be discontinuous (e.g., square wave), despite requiring it to be of unknown integer multiples of certain period. Typically, the multi‐agent systems admit more than one ingredient causing heterogeneities: (i) No identical requirement is made on the system nonlinearities and input directions (the unknown signs of the input coefficients). (ii) The orders of agent dynamics can be different (the dynamics are first‐order, second‐order, or even high‐order). Nevertheless, in the context, we still pursue the asymptotic output consensus, and unlike some related literature, instead of seeking a time‐varying strategy which means the introduction of infinitely large gains, we combine a refined switching strategy with continuous adaptive one together to propose a new consensus protocol. It turns out that under the proposed protocol, all the agent outputs reach a common value while all the closed‐loop signals are bounded. Simulation examples are given to demonstrate the effectiveness of the proposed protocol. [ABSTRACT FROM AUTHOR]

In this paper, the $ H_{\infty } $ H ∞ consensus problem of stochastic nonlinear multi-agent systems with time-delay, Markov jump and $ (x, u, v) $ (x , u , v) -dependent noises is studied. Firstly, the $ H_{\infty } $ H ∞ consensus problem is transformed into a standard $ H_{\infty } $ H ∞ control problem by model transformation. Then, a dynamic output feedback control protocol is constructed by solving a set of linear matrix inequalities to ensure that the closed-loop system achieves the mean square consensus and meets the specified $ H_{\infty } $ H ∞ performance level. After that, both delay-independent and delay-dependent stochastic bounded real lemmas are established by taking advantage of the Lyapunov–Krasovskii function method and the generalised It $ \hat {\rm {o}} $ o ^ formula. Finally, we illustrate the validity of the developed method with numerical simulations. [ABSTRACT FROM AUTHOR]

In this article, a distributed energy management strategy is proposed for smart grid with stochastic wind power. The different Weibull probability distribution function (PDF) of wind power during different operation intervals, coupled with ramp rate limits of thermal generators across operation intervals, is considered in this operation cost optimization problem. Under multiagent system communication framework, we first decompose the problem into subproblems associated to operation interval. For each operation interval, parameters of Weibull PDF are estimated by maximum likelihood method according to wind speed obtained by wind speed forecast model of committed wind turbine. Then, a consensus-based alternating direction method of multipliers (ADMM) is proposed to get the optimal operation plan for all committed generators, where Armijo line search algorithm is employed to adaptively obtain the step size in the iterations. The simulation results show that the proposed consensus-based ADMM outperforms distributed projected gradient method in previous study on energy management with wind power; the proposed distributed strategy is valid for short-term energy management for smart grid with stochastic wind power. [ABSTRACT FROM AUTHOR]

LaSalle theorems, sometimes called as invariance-like theorems, have witnessed abundant applications as powerful tools of analysing system convergence. However, these theorems have twofold limitations: On the one hand, the uniformity of convergence with respect to initial state values cannot be offered, which indicates that the possibility of excessively slow convergence could not be ruled out for a given bounded set of initial state values. On the other hand, unbounded time-variations are not allowed in the systems, and meanwhile, the boundedness of all the states are required even if one merely concerns the convergence of partial states, precluding many scenarios with the unboundedness (e.g., induced by stochastic noise) for some states defined on the whole time horizon. Towards the limitations of LaSalle theorems, this paper seeks to further develop convergence theorems in the stochastic framework. First, a Lyapunov-like function based theorem on the convergence owning the uniformity with respect to initial state values is presented for Itô-type stochastic systems, with the infinitesimal of Lyapunov-like functions exploited more delicately than those in stochastic LaSalle theorems. Based on this, a framework of adaptive stabilization with the uniformity of convergence is established for uncertain stochastic nonlinear systems. In particular, the performance specifications involved are impossible to achieve by applying LaSalle theorems as in the related results. Second, an enlarged convergence theorem is established with Lyapunov-like conditions moderately relaxed, which allows the unboundedness for partial states defined on the whole time horizon and has potential applications in the presence of unbounded time-variations. What is notable, the enlarged convergence theorem is nontrivial to verify, which compels us to propose an extended Barbălat lemma with the conventional requirement of uniform continuity relaxed in the stochastic framework. [ABSTRACT FROM AUTHOR]

Summary: This article is devoted to global adaptive stabilization for a class of uncertain nonlinear systems. Notably, the systems under investigation admit unknown control directions and unknown input powers, and particularly the latter, which are a new type of system uncertainties, largely challenge the feasibility of continuous feedbacks. This spurs us to pursue a switching adaptive feedback which is actual a discontinuous one with high feedback capability. To solve the control problem, a parameterized controller in a specified form is first introduced, which can globally stabilize the system once the design parameter involved belongs to a certain set. However, the controller cannot directly be implemented since the set depends heavily on the unknown input powers. To make the parameterized controller implementable, a new switching strategy is delicately proposed, which can instantly update the parameters of the controller to compensate the serious system uncertainties. It turns out that the parameterized controller with switching updating mechanism guarantees that all the signals of the closed‐loop system are globally bounded and ultimately converge to zero. Simulation examples demonstrate the effectiveness of the proposed design scheme. [ABSTRACT FROM AUTHOR]

Summary: This article is devoted to the global practical tracking for a class of uncertain nonlinear systems. Notably, the input powers of the system are unknown and not required to be upper bounded by known constants. This means the presence of new type of serious uncertainties, which makes the problem under investigation largely challenging and urges us to develop a new powerful adaptive control scheme, particularly the compensation strategy to overcome the negative influence caused by the uncertainties. For this, a dual high‐gain‐based adaptive control design scheme is proposed, in which a dynamic high gain and a high gain function are jointly introduced to compensate the serious system uncertainties. Under the designed controller, all the signals of the resulting closed‐loop system are bounded and furthermore the tracking error remains any prescribed small after a finite time. [ABSTRACT FROM AUTHOR]

Summary: Adaptive output‐feedback control is investigated for a class of uncertain damped wave equations. The remarkable features of the system in question are as follows: (i) Unknown damping is allowed at the boundary; (ii) The boundary measurement is corrupted by an unknown harmonic disturbance. These features make the control problem essentially different from those in the related literature. To solve the problem, a novel adaptive output‐feedback control scheme is established for the system. Specifically, an ingenious observer is first introduced to reconstruct the unmeasured system state in the space domain. Based on this, a certain compensation mechanism is designed for the unknown damping coefficient and output disturbance by adaptive technique based on projection operator. Then, an output‐feedback controller is successfully designed by the backstepping method for ODEs, which guarantees that all states of the resulting closed‐loop system are bounded, and the original system state ultimately converges to an arbitrarily prescribed small neighborhood of the origin. Finally, a simulation example is provided to illustrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper is devoted to the boundary stabilisation via event-triggered output-feedback for a class of 2 × 2 hyperbolic systems. Different from the closely related works, the system parameters are spatially varying and only one boundary measurement is available for feedback, which brings essential difficulties to the analysis and synthesis of event-triggered control. To solve the problem, by using the time-varying strategy and the infinite-dimensional backstepping technique, a novel event-triggered output-feedback controller is designed for the systems. Particularly, a time-varying event-triggering mechanism, with an extra decaying signal introduced into the threshold, is determined. It is rigorously shown that the designed event-triggered controller can guarantee that all the states of the resulting closed-loop system exponentially converge to zero in the sense of L 2 norm while no Zeno phenomenon occurs. Two simulation examples are given to illustrate the effectiveness of the established boundary control strategy. [ABSTRACT FROM AUTHOR]

Adaptive stabilisation is investigated for a class of uncertain coupled parabolic equations in this paper. The presence of unknown coefficients can reduce the rigorousness of system modelling and enlarge the scope of the systems, whereas it could give rise to essential difficulties to control problems. Mainly due to the latter, certain new initiative, such as uncertainty compensation, should be considered to solve the stabilisation problem. For this, by infinite-dimensional backstepping method combining with adaptive compensation technique, an adaptive control scheme is proposed. Then, an adaptive state-feedback controller is constructed which guarantees that all the closed-loop system states are bounded while the original system states converge to zero. A numerical example is provided to validate the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

This paper reviews the genealogy of 'Chinese' political geography, which, to a certain extent, can be read as a national report of the status of political geography in Chinese scholarship. It begins by outlining the short duration of the development of political geography in China, compared to the longer history of western political geography. Looking at the extant studies related to political geography in China, this paper suggests an existence of a duality in this field. One strand of scholarship is termed 'exogenous political geography', which is largely influenced by western scholarship with a particular focus on theories and vocabularies from classical geopolitics and geo-economy. The other strand is termed as 'endogenous political geography', which covers rich topics, including, yet not limited to, political and geographical views of inter-state relationships, central-local relationships and emperor-people relationships. Such a duality is important for understanding the condition of current political geography in China. The dualised understanding, however, seems to have undermined the comprehensiveness of political geography in China. In this regard, this paper calls for a more complete, integrated and critical agenda for political geography in China. [ABSTRACT FROM AUTHOR]

This paper considers the global stabilization for a class of uncertain nonlinear systems with unknown powers, unknown control directions, and unknown nonlinearities. Mainly due to the presence of the unknown powers which have not known upper bound, no existing methods are applicable to the control problem to be solved. In this paper, to compensate the serious system uncertainties and particularly to overcome the major obstruction from unknown powers, we appeal to the mechanism of switching adaptive feedback. By flexibly combining the domination and the method of adding a power integrator, we propose a new adaptive controller design, whose design parameters are tuned online based on a switching logic. The designed controller will become operative as long as finite switchings happen and will not lead to Zeno phenomenon, and can guarantee the global boundedness as well as ultimate convergence of the resulting closed-loop system. Two numerical examples are given to demonstrate the effectiveness of the developed design scheme. [ABSTRACT FROM AUTHOR]

Summary: This paper is concerned with the global output feedback stabilization for a class of nonholonomic systems with unknown parameter, polynomial‐of‐output, and unmeasurable states dependent growth. A dynamic high‐gain observer is first designed to reconstruct the unmeasurable system states and, in addition, to compensate the serious parameter unknowns in nonlinear drifts. Then, we design a compact adaptive controller without invoking the backstepping technique, which reduces the complexity of controller. Additionally, a switching control strategy is employed to overcome the smooth feedback obstacle associated with nonholonomic systems. It is shown that the proposed control laws guarantee that all closed‐loop system states are globally bounded and ultimately converge to zero. The simulation results demonstrate the effectiveness of the proposed control strategy. [ABSTRACT FROM AUTHOR]

This paper is devoted to the global output-feedback stabilisation for a class of nonlinear systems with inherent nonlinearities and coarse disturbance. Remarkably, the disturbance may be non-periodic, non-differentiable and/or of unknown magnitude, and hence some critical requirements on the disturbance in the existing related literature are successfully removed. Recognising that the strategies of disturbance compensation, such as internal model principle, sliding mode control method, learning method and active disturbance rejection control method, are quite hard or even impossible to apply, a time-varying design scheme is developed in the paper. Moreover, the serious unknowns and time-variations reflected in the growth rate of the system are also dealt with by the proposed scheme. By designing a time-varying output-feedback controller, all the signals of the resulting closed-loop system are globally bounded, and the original system state and the observer state ultimately converge to zero. [ABSTRACT FROM AUTHOR]

This paper is devoted to the stabilization for a class of uncertain linearized Ginzburg–Landau equations (GLEs). The distinguishing feature of such system is the presence of serious uncertainties which enlarge the scope of the systems whereas challenge the control problem. Therefore, certain dynamic compensation mechanisms are required to overcome the uncertainties of system. Motivated by the related literature, the original complex-valued GLEs are transformed into a class of real-valued coupled parabolic systems with serious uncertainties and distinctive characteristics. For this, two classes of identifiers respectively based on passive and swapping identifiers are first introduced to design parameter dynamic compensators. Then, by combining infinite-dimensional backstepping method with the dynamic compensators, two adaptive state-feedback controllers are constructed which guarantee all the closed-loop system states are bounded while the original system states converge to zero. A numerical example is provided to validate the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

Abstract This paper addresses the problem of global adaptive stabilization by output-feedback for a class of uncertain nonlinear systems with unknown growth rate and unknown output function. By constructing a suitable Lyapunov function, a new systematic design scheme is proposed to derive an adaptive output-feedback controller with appropriate design parameters based on a dynamic high-gain, under which the system states can be globally regulated to zero. Because the proposed method uses the adaptive technique rather than the time-varying one, it does not require a priori known information about either the growth rate or the upper and lower bounds of the derivative of the unknown output function. This makes the investigated system substantially different from the existing results and also highlights the main contributions of the paper. A practical example is presented to show the validity of the theoretical results. [ABSTRACT FROM AUTHOR]

In this paper, finite-time consensus tracking is investigated via time-varying feedback for uncertain nonlinear multi-agent systems (NMASs). The presence of inherent uncertainties and disturbances in the NMASs highlights the main novelty : (1) The inherent uncertainties imply that more serious unknowns and time-variations are allowed in the nonlineartities and the control coefficients of the NMASs. (2) The inherent disturbances mean that the upper bound of the disturbances is unknown. To compensate the inherent uncertainties and disturbances, time-varying protocols are proposed by integrating time-varying technique and sliding mode method. Based on the proposed protocols, the finite-time leader-following consensus and finite-time containment are achieved under directed graph. Finally, the validation of the proposed protocols is verified by two examples. [ABSTRACT FROM AUTHOR]

In the near future, plug-in electric vehicles (PEVs) will dominate the car market. The peak-valley difference would increase greatly due to the random nature of PEVs charging behaviors. In this paper, a new problem on studying the dynamic economic/emission dispatch (DEED) including PEVs for peak shaving and valley filling is proposed, and furthermore, the effect caused by different vehicle-to-grid (V2G) and grid-to-vehicle (G2V) loads on DEED is analyzed. The optimization model of the problem is constructed including several practical constraints, such as power flow constraints and ramp rate limits. The battery degradation cost is also included, which reshapes the objective function of DEED. Based on the model, a strategy for DEED including PEVs for peak shaving and valley filling is given, and a multiobjective optimization algorithm is adopted to solve the proposed problem. To demonstrate the feasibility and effectiveness of the proposed strategy, three DEED cases are considered under different V2G power. The analysis of the effect on fuel cost and emission caused by different V2G power shows that the proposed strategy can effectively reduce the emission and cut down the investment in peak load plants. [ABSTRACT FROM AUTHOR]

This paper considers the global output-feedback stabilisation for power integrator systems with unknown control direction. The presence of uncontrollable and unobservable linearisation renders the strategy based on Nussbaum function rather difficult (even impossible) to compensate the unknown control direction. In this paper, to dominate the inherent nonlinearities and unknowns, a powerful switching strategy is proposed by combining an output-feedback scheme and a switching mechanism. First, a special case with known control direction is considered to provide a basic structure and selection rules of design parameters for the expected controller, and then, the essential case with unknown control direction is investigated to build a suitable switching logic to online tune the design parameters. The proposed switching-type output-feedback controller guarantees that all the system signals are globally bounded and ultimately converge to zero. A numerical example is given to illustrate the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

Abstract This paper is devoted to the global stabilization and practical tracking for a class of uncertain nonlinear systems. The presence of unknown powers and serious parameter unknowns makes the systems in question essentially different from those in the related works. By skillfully combining adaptive technique and adding a power integrator, two novel adaptive state-feedback controllers are successfully designed to achieve global stabilization and practical tracking, respectively. Remarkably, the typical feature of the two controllers lies in the introduction of the adaptive dynamic and the terms of lower and higher powers (with respect to the unknown system powers), which makes the controller powerful enough to compensate the serious parameter unknowns and the unknown powers of the system. Finally, simulation examples are provided to illustrate the effectiveness of the designed controllers. [ABSTRACT FROM AUTHOR]

Multiple uncertainties/noises, frequently exist in a plant, usually require multiple compensation techniques, which renders feedback controllers highly dynamic and nonlinear. This motivates us to search for a compact design scheme of compensation to reduce the complexity of controllers. In this paper, global output-feedback stabilisation is investigated for a class of uncertain nonlinear systems with unknown unmeasured states-dependent growth and input matching uncertainty. To solve the problem, a compact scheme is proposed to design a global adaptive output-feedback controller, which combines the technique of dynamic gain and extended state observer together. Particularly, only one dynamic gain, rather than two dynamic gains, is introduced to deal with the unknown polynomial-of-output growth rate, which makes our controller to have lower dynamics than those in the related works. Moreover, the input matching uncertainty is asymptotically estimated by the extended state observer, and thus its effect is well counteracted. It is shown that, under the designed controller, the system states globally converge to zero. A simulation example on non-zero set-point regulation demonstrates the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

Adaptive stabilisation is investigated for ordinary differential equation systems via distributed effect of uncertain diffusion-dominated actuator dynamics. The presence of the unknowns/uncertainties and the distributed effect makes the system under investigation more general and representative than those of the related literature, and moreover yields the ineffectiveness of the existing methods on this topic. By constructing an invertible spatial and time-varying state transformation, the original closed-loop system is first changed into a target system, from which the design of parameter updating law and the analysis of the closed-loop system performance become more convenient. Then, by Lyapunov method and adaptive compensation technique, an adaptive stabilising controller is successfully constructed, which guarantees that the original system states converge to zero while other closed-loop system states are bounded. A simulation example is provided to validate the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, a multiobjective hybrid bat algorithm is proposed to solve the combined economic/emission dispatch problem with power flow constraints. In the proposed algorithm, an elitist nondominated sorting method and a modified crowding-distance sorting method are introduced to acquire an evenly distributed Pareto Optimal Front. A modified comprehensive learning strategy is used to enhance the learning ability of population. Through this way, each individual can learn not only from all individual best solutions but also from the global best solutions (nondominated solutions). A random black hole model is introduced to ensure that each dimension in current solution can be updated individually with a predefined probability. This is not only meaningful in enhancing the global search ability and accelerating convergence speed, but particularly key to deal with high dimensional systems, especially large-scale power systems. In addition, chaotic map is integrated to increase the diversity of population and avoid premature convergence. Finally, numerical examples on the IEEE 30-bus, 118-bus and 300-bus systems, are provided to demonstrate the superiority of the proposed algorithm. [ABSTRACT FROM AUTHOR]